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yunjey
2017-05-23 16:33:36 +09:00
parent 3923f4df6c
commit 47d70f91ac
11 changed files with 22 additions and 22 deletions
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4
tutorials/02 - Logistic Regression/main.py
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@ -13,12 +13,12 @@ batch_size = 100
learning_rate = 0.001
# MNIST Dataset (Images and Labels)
train_dataset = dsets.MNIST(root='../data',
train_dataset = dsets.MNIST(root='./data',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data',
test_dataset = dsets.MNIST(root='./data',
train=False,
transform=transforms.ToTensor())

4
tutorials/03 - Feedforward Neural Network/main-gpu.py
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@ -14,12 +14,12 @@ batch_size = 100
learning_rate = 0.001
# MNIST Dataset
train_dataset = dsets.MNIST(root='../data',
train_dataset = dsets.MNIST(root='./data',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data',
test_dataset = dsets.MNIST(root='./data',
train=False,
transform=transforms.ToTensor())

4
tutorials/03 - Feedforward Neural Network/main.py
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@ -14,12 +14,12 @@ batch_size = 100
learning_rate = 0.001
# MNIST Dataset
train_dataset = dsets.MNIST(root='../data',
train_dataset = dsets.MNIST(root='./data',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data',
test_dataset = dsets.MNIST(root='./data',
train=False,
transform=transforms.ToTensor())

4
tutorials/04 - Convolutional Neural Network/main-gpu.py
View File

@ -11,12 +11,12 @@ batch_size = 100
learning_rate = 0.001
# MNIST Dataset
train_dataset = dsets.MNIST(root='../data/',
train_dataset = dsets.MNIST(root='./data/',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data/',
test_dataset = dsets.MNIST(root='./data/',
train=False,
transform=transforms.ToTensor())

4
tutorials/04 - Convolutional Neural Network/main.py
View File

@ -11,12 +11,12 @@ batch_size = 100
learning_rate = 0.001
# MNIST Dataset
train_dataset = dsets.MNIST(root='../data/',
train_dataset = dsets.MNIST(root='./data/',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data/',
test_dataset = dsets.MNIST(root='./data/',
train=False,
transform=transforms.ToTensor())

4
tutorials/05 - Deep Residual Network/main-gpu.py
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@ -16,12 +16,12 @@ transform = transforms.Compose([
transforms.ToTensor()])
# CIFAR-10 Dataset
train_dataset = dsets.CIFAR10(root='../data/',
train_dataset = dsets.CIFAR10(root='./data/',
train=True,
transform=transform,
download=True)
test_dataset = dsets.CIFAR10(root='../data/',
test_dataset = dsets.CIFAR10(root='./data/',
train=False,
transform=transforms.ToTensor())

4
tutorials/05 - Deep Residual Network/main.py
View File

@ -16,12 +16,12 @@ transform = transforms.Compose([
transforms.ToTensor()])
# CIFAR-10 Dataset
train_dataset = dsets.CIFAR10(root='../data/',
train_dataset = dsets.CIFAR10(root='./data/',
train=True,
transform=transform,
download=True)
test_dataset = dsets.CIFAR10(root='../data/',
test_dataset = dsets.CIFAR10(root='./data/',
train=False,
transform=transforms.ToTensor())

4
tutorials/06 - Recurrent Neural Network/main-gpu.py
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@ -16,12 +16,12 @@ num_epochs = 2
learning_rate = 0.01
# MNIST Dataset
train_dataset = dsets.MNIST(root='../data/',
train_dataset = dsets.MNIST(root='./data/',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data/',
test_dataset = dsets.MNIST(root='./data/',
train=False,
transform=transforms.ToTensor())

4
tutorials/06 - Recurrent Neural Network/main.py
View File

@ -16,12 +16,12 @@ num_epochs = 2
learning_rate = 0.01
# MNIST Dataset
train_dataset = dsets.MNIST(root='../data/',
train_dataset = dsets.MNIST(root='./data/',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data/',
test_dataset = dsets.MNIST(root='./data/',
train=False,
transform=transforms.ToTensor())

4
tutorials/07 - Bidirectional Recurrent Neural Network/main-gpu.py
View File

@ -16,12 +16,12 @@ num_epochs = 2
learning_rate = 0.003
# MNIST Dataset
train_dataset = dsets.MNIST(root='../data/',
train_dataset = dsets.MNIST(root='./data/',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data/',
test_dataset = dsets.MNIST(root='./data/',
train=False,
transform=transforms.ToTensor())

4
tutorials/07 - Bidirectional Recurrent Neural Network/main.py
View File

@ -16,12 +16,12 @@ num_epochs = 2
learning_rate = 0.003
# MNIST Dataset
train_dataset = dsets.MNIST(root='../data/',
train_dataset = dsets.MNIST(root='./data/',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='../data/',
test_dataset = dsets.MNIST(root='./data/',
train=False,
transform=transforms.ToTensor())